Statistical Analysis of Efficient Unbalanced Factorial Designs for Two-Color Microarray Experiments
Author
Source
International Journal of Plant Genomics
Issue
Vol. 2008, Issue 2008 (31 Dec. 2008), pp.1-16, 16 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2008-06-18
Country of Publication
Egypt
No. of Pages
16
Main Subjects
Abstract EN
Experimental designs that efficiently embed a fixed effects treatment structure within a random effects design structure typically require a mixed-model approach to data analyses.
Although mixed model software tailored for the analysis of two-color microarray data is increasingly available, much of this software is generally not capable of correctly analyzing the elaborate incomplete block designs that are being increasingly proposed and used for factorial treatment structures.
That is, optimized designs are generally unbalanced as it pertains to various treatment comparisons, with different specifications of experimental variability often required for different treatment factors.
This paper uses a publicly available microarray dataset, as based upon an efficient experimental design, to demonstrate a proper mixed model analysis of a typical unbalanced factorial design characterized by incomplete blocks and hierarchical levels of variability.
American Psychological Association (APA)
Tempelman, Robert J.. 2008. Statistical Analysis of Efficient Unbalanced Factorial Designs for Two-Color Microarray Experiments. International Journal of Plant Genomics،Vol. 2008, no. 2008, pp.1-16.
https://search.emarefa.net/detail/BIM-482760
Modern Language Association (MLA)
Tempelman, Robert J.. Statistical Analysis of Efficient Unbalanced Factorial Designs for Two-Color Microarray Experiments. International Journal of Plant Genomics No. 2008 (2008), pp.1-16.
https://search.emarefa.net/detail/BIM-482760
American Medical Association (AMA)
Tempelman, Robert J.. Statistical Analysis of Efficient Unbalanced Factorial Designs for Two-Color Microarray Experiments. International Journal of Plant Genomics. 2008. Vol. 2008, no. 2008, pp.1-16.
https://search.emarefa.net/detail/BIM-482760
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-482760